Evolutionary multi-objective workflow scheduling in Cloud
- Submitting institution
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The University of Birmingham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 91072666
- Type
- D - Journal article
- DOI
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10.1109/TPDS.2015.2446459
- Title of journal
- IEEE Transactions on Parallel and Distributed Systems
- Article number
- -
- First page
- 1344
- Volume
- 27
- Issue
- 5
- ISSN
- 1045-9219
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2015
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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-
- Citation count
- 125
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Workflow scheduling techniques in traditional distributed/heterogeneous computing face difficulties in cloud environments since the cloud is characterised by service-based resource managing and pay-per-use pricing.
This paper models workflow scheduling in the cloud as a bi-objective optimisation problem of minimising makespan and cost, and customises an evolutionary algorithm to tackle it, through designing a series of problem-specific search operators. The results were successfully validated against state-of-the-art QoS scheduling algorithms.
Since its publication in the top distributed and high-performance computing journal, it is the fourth most cited papers (out of 999) in that journal.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -